GraphPed 0.0.2

A pedigree visualization tool based on dot format and visualized by graphviz

GraphPed: a novel graph-based visualization method for large and complex pedigrees

author: Yin Huang

citation:

Install

pip install graphped

How to use

1. In command line

!GraphPed -h

• 1. standard pedigrees in the ped file

GraphPed -p data/example_fam.ped -o data/cli/ -f pdf

• 2. extended pedigrees in the ped file

GraphPed -p data/example_fam_ext.ped -o data/cli/ -f svg -a data/default.yaml 

2.In jupyter notebook

from graphped.plot import *

fam=readped('data/example_fam.ped')
plotped(fam)

Or

show(GraphPed(fam))

GraphPed function can plot all the pedigrees in the fam dataframe.

Adding self-defined attributes. the number of traits in the input file should match with the number of traits in the attribute yaml file.

attrs=load_attributes('data/default.yaml')
famext=readped('data/example_fam_ext.ped',attrs)
plotped(famext,attrs)

Write to output folder with pdf format

plotped(famext,attrs,output='data/jpn',format='pdf')

Or output multiple pedigrees.

GraphPed(famext,attrs,output='data/jpn',format='pdf')

Tutorial

Setting the attribute yaml file

• reference:
  • fillcolor https://graphviz.org/docs/attrs/fillcolor/
  • style https://graphviz.org/docs/attrs/style/
  • fontcolor https://graphviz.org/docs/attrs/fontcolor/
  • … https://graphviz.org/doc/info/attrs.html

For one trait ped file, if the trait values are affected status, which should be coded as follows: -9 or 0 is missing,1 is unaffected, and 2 is affected. you don’t need to set the attribute file. Otherwise, you need to set your attribute file by following:

The format of the attribute of yaml file

trait name:
    attribute name:
        (the pairs of tait value and attribute value)
        tait value1: attribute value1
        tait value2: attribute value2
        ...

If you have more than one traits, you need to set each trait separately in the yaml file. The following is an example.

trait1:
    fillcolor:
        1: 'white'
        2: 'dimgrey'
        -9: 'aquamarine3'

trait2:
    style:
        True: filled,setlinewidth(4)
        False: filled
    

trait3:
    fontcolor:
        True: darkorange
        False: black

attrs=load_attributes('data/default.yaml')

attrs

Two example pedigrees

one is standard, one is extended with 3 traits.

Standard ped file

Fam F4  P3  F1  1   1
Fam F3  P3  F1  2   1
Fam F2  P3  F1  2   1
Fam F1  P1  P2  2   2
Fam P3  0   0   1   2
Fam P1  0   0   1   -9
Fam P2  0   0   2   -9

fam=readped('data/example_fam.ped')

fam

plotped(fam)

plotped(fam)

Extended ped file

Fam1    F4  P3  F1  1   1   True    False
Fam1    F3  P3  F1  2   1   True    True
Fam1    F2  P3  F1  2   1   True    False
Fam1    F1  P1  P2  2   2   True    False
Fam1    P3  0   0   1   2   True    False
Fam1    P1  0   0   1   -9  False   True
Fam1    P2  0   0   2   -9  False   True

famext=readped('data/example_fam_ext.ped',attrs)

famext

plotped(famext,attrs)

dots=GraphPed(fam)

show(dots)

Write out plots

plotped(fam,output='data/exampleplots',format='png')

Show the plot from data/exampleplots/Fam.png

Real data examples

all_fam=readped('data/Fig_2_3_fam.ped')

all_fam

Fig.1 The workflow of GraphPed

show workflow

Fig.2 The pedigrees of complex families

plotped(all_fam[all_fam.fid=='25_2'])

Fig.S2 The largest pedigree in ADSP

plotped(all_fam[all_fam.fid=='4_649'])

Fig.3 The pedigrees with incorrect information

plotped(all_fam[all_fam.fid=='10R_R99'])

Fig.4 The pedigrees with multiple phenotypes

self-defined multiple-trait yaml

ad:
    fillcolor:
        1: 'white'
        2: 'dimgrey'
        -9: 'aquamarine3'

vcf:
    style:
        True: filled,setlinewidth(4)
        False: filled
    

trim:
    fontcolor:
        True: darkorange
        False: black

attrs=load_attributes('data/self_defined_mutiple_traits.yaml')
ped=readped('data/Fig4_fam_ext.ped',attrs)

ped

plotped(ped,attrs)

Show multiple figures with self-defined attributes

self-defined single-trait yaml

ad:
    fillcolor:
        1: 'white'
        2: 'dimgrey'
        -9: 'aquamarine3'

attr=load_attributes('data/self_defined_single_trait.yaml')
all_fam=readped('data/Fig_2_3_fam.ped',attr)

all_fam

dots=GraphPed(all_fam,attr)
show(dots)